Visual Summarization Analysis

Problem Solved

Videos and images often contain subjects, actions, backgrounds, and text cues, but converting them into natural-language descriptions is labor-intensive. visual-summary-analysis turns this visual-content understanding task into a scripted workflow: given a local image or video file or a public URL, it generates a coherent scene summary and supports cloud-based historical report queries.

How It Works

• Input: supports jpg/jpeg/png/mp4/avi/mov up to 10MB; video clips should preferably stay under 5 minutes, with clear, unobstructed subjects.
• Analysis: the bundled scripts.visual_summary_analysis module calls the API, recognizes scene content, objects, actions, and text, then integrates them into a Chinese description.
• Querying: historical reports are read only through --list from the cloud API and rendered as a Markdown table; local memory or long-term memory must not be used.
• Identity: the system handles identity association internally without asking users for, or exposing, internal identity parameters.

Boundaries

It fits video content understanding, accessibility assistance, and media asset summarization. Results may be unstable for blurry input, overly long clips, heavily occluded subjects, files larger than 10MB, or private non-public URLs; URL processing should use publicly accessible addresses.